Data is the new soil of business and (soon) at the core of essentially all domains from material science to healthcare. Mastering big data not only requires skills in a variety of disciplines from distributed systems over statistics to machine learning, but also requires an understanding of a complex ecosystem of tools and platforms. This seminar will try to shed some light into the complex space of data science covering aspects from data management, distributed algorithms, virtualization, data mining, machine learning, and statistics. We will discuss how these techniques complement each other to make sense of data at massive scale.Prerequisite: CS 32 and 127, or equivalents, or instructor permission.

Sensor networks combine sensing, computing, actuation, and communication in a single infrastructure that allows us to observe and respond to phenomena in the physical and cyber world. The sensors range from tiny ‘smart dusts’ to dime-sized RFID tags and large-scale weather sensors. This course will cover the state-of-the art in designing and building sensor networks, focusing on issues that revolve around data and resource management.Prerequisite: None

This course explores data and resource management issues that arise in the design, implementation, and deployment of networked information systems by covering the state of the art in research and industry. Topics include mobile data access and dissemination, sensor networks, and Internet-scale information systems and services.Prerequisites: CS 138 or permission of the instructor

Enabling visual data exploration at “human speed” is key to democratizing data science and maximizing human productivity. Unfortunately, traditional data management systems like PostgreSQL, Microsoft SQL Server, or more recent analytical frameworks, like Hadoop, Spark, and many others, are ill-suited for that purpose. This seminar course will cover the State-of-The-Art data exploration systems that better support the requirements of interactive data explorations; students are expected to build a prototype data exploration tool, and write a short research paper on their contributions.Prerequisites: One of CSCI 0320, CSCI 0330; and one of CSCI 1270, CSCI 1951-A, CSCI 1670 or permission of the instructor